Senior Data Engineer

GLS/NXT

Senior Data Engineer at GLS/NXT focusing on data infrastructure and analytics platform reliability. Collaborating across teams to drive quality and scalability in data solutions.

Posted 7/19/2026full-timeBerlin • 🇩🇪 GermanySeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and scaling data engineering pipelines, utilizing modern programming languages like Python and Go, and leveraging cloud platforms such as AWS and GCP. Proficient in data warehousing technologies and workflow orchestration tools to ensure data quality and effective project management.

Highest-signal resume keywords

Data Engineering Pipeline DesignApache AirflowAWS Cloud PlatformGoogle BigQuerySQL Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData ModelingSchema DesignIncremental StrategiesQuery OptimizationLookerLookMLCI/CD PipelinesAgile MethodologiesData Quality Best Practices

Soft Skills

Strong English CommunicationHighly OrganizedProject ManagementTask Prioritization

Tools & Technologies

Apache AirflowAWSGCPGoogle BigQuerySnowflakeDBT

Industry Keywords

Data WarehousingData InfrastructureCross-Functional CollaborationData ApplicationsSystems Documentation

Tech Stack

Tools & technologies

AirflowApacheAWSBigQueryCloudGoGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Collaborate across functions to scale GLS/NXT data infrastructure
Contribute to the roadmap and development of GLS/NXT data products
Design, build, monitor, and scale data pipelines for Data Warehousing, integrating various data sources and destinations
Develop data models and schemas supporting analytical requirements
Work with other engineering teams to resolve architecture and infrastructure challenges, designing effective solutions
Participate in cross-functional projects supporting data applications and reporting
Address data quality issues, implementing best practices
Create and maintain comprehensive systems documentation

Requirements

What you’ll need

Bachelor's degree in Computer Science or a related engineering field
5+ years of proven experience in data engineering roles
Expertise in designing, building, monitoring, and scaling data engineering pipelines
Hands-on experience with workflow orchestration tools such as Apache Airflow for designing, scheduling, and managing complex data pipelines
Proficient in modern data programming languages, including Python and Go
Extensive hands-on experience with cloud platforms, specifically AWS and GCP
Proficient with data warehousing technologies, including Google BigQuery and Snowflake
Proficient in SQL for diverse data sources, leveraging tools such as DBT for data modeling, schema design, incremental strategies, and query optimization
Looker and LookML expertise, with a focus on data preparation and modeling to support analysis and efficient visualizations
Software development operations management experience, including CI/CD pipelines, grounded in agile methodologies
Strong English communication skills for effective cross-functional collaboration
Highly organized with the ability to prioritize tasks and manage projects aligned to business goals
Skilled at setting clear priorities to drive project success

Benefits

Comp & perks

Dynamic workplace: A digital environment with international projects and space to learn and grow
Flexible work conditions: Hybrid working mode with a tailored remote policy
Focus on learning: A personal budget (1.000€) for learning and development initiatives
Physical space for ideas: A great office space in Berlin Mitte with top-tier equipment
Transparent and competitive compensation: A salary package that reflects your expertise and experience
Active participation: A clear bonus system enabling participation in your and the team’s performance
Engaging team culture: Monthly team cooking, regular events and offsites
Vacation policy: 30 days of yearly holiday
Reward system: Rewards for the recommendation of additional team members